Finding information about people in the World Wide Web is one of the most common activities of Internet users. Person names, however, are highly ambiguous. In most cases, the results for a person name search are a mix of pages about different people sharing the same name. The user is then forced either to add terms to the query (probably losing recall and focusing on one single aspect of the person), or to browse every document in order to filter the information about the person he/she is actually looking for. In an ideal system the user would simply type a person name, and receive search results clustered according to the different people sharing that name.
In 2007 the Web People Search Task was the first competitive evaluation focused on this problem. The 16 participating systems received a set of web pages for a person name, and they had to cluster them into different entities. This second evaluation provides a new testbed corpus, improved evaluation metrics, and an additional attribute extraction subtask. These are the task definitions:
- Clustering - In this task systems receive as input a set of web search results obtained when performing a query for an (ambiguous) person name. The expected output is a clustering of the web pages, where each cluster is assumed to contain all (and only those) pages that refer to the same individual.
- Attribute Extraction - This subtask consists of extracting 18 kinds of "attribute values" for target individuals whose names appear on each of the provided Web pages. The organizers will distribute the target Web pages in their original format (i.e., html), and the participant systems have to extract attribute values from each page.
Please send an email expressing your interest to the task organizers (email@example.com).
- October 2008: Distribute the training data + CFP
- December 1-8, 2008: Evaluation
- December 17, 2008: Return the evaluation result
- February 2009: Papers due.
- April 2x, 2009: Workshop in Madrid.